How to describe columns as categorical values?

Question

I have a pandas dataframe that contains a mix of categorical and numeric columns. By default, df.describe() returns only a summary of the numerical data (describing those columns with count, mean, std, min, quantiles, max)

when iterating through all the columns in the df and describing them individually as [df[c].describe() for c in df.columns] the description is returned based off of specific column dtype; i.e. numerical summary for int and float and categoric summary for object

Does any one know of a succinct way of describing all columns as categorical with count, unique, top, freq?

Couperin

I think I answered myself while clarifying the question. just tried df.astype('object').describe() and it works!! – Couperin

moving my comment to an answer for future reference! – Couperin

Answer 1

following converts all columns to object type then describes them:

df.astype('object').describe()

for cleaner view try:

df.astype('object').describe().transpose()

Couperin

Thank you so much! By the way, for shorter code, try T instead of transpose() – Neves

Answer 2

a slightly shorter version of the answer:

df.describe(include = 'object')

Tillis

Answer 3

Additionally, if YOU want to see descriptions of all columns together(including categorical). you can use:

df.describe(include='all')

Antiquary